Computational Phonology

Humans intuitively pattern meaningless symbolic elements into meaningful units when we comprehend and produce language. The rules and structures governing this patterning - phonology - act as a cognitive filter for the underlying structure of language as it is transformed into external action, whether through speech, sign, or tactile language. The wide variety of patterns that humans produce across languages, and their mappings from underlying forms to surface forms, show a remarkable computational simplicity, combined with efficient and accurate learning algorithms. I draw on automata theory, formal language theory, grammatical inference, and mathematical logic to clarify the nature of the human mental capacity of phonology.


No Free Lunch in Linguistics or Machine Learning. (with J. Heinz). To appear in Language

Subregular Complexity Across Speech and Sign. Qualifying Paper, Stony Brook University, 2017 

Phonological Complexity is Subregular: Evidence from Sign language. Proceedings of the 51st Meeting of the Chicago Linguistics Society.


Learnability in Phonology. (with J. Heinz). to appear in H. van der Hulst and B. Elan Dresher (eds.) Oxford Handbook of the History of Phonology

Learning with Partially Ordered Representations. (with J. Chandlee, R. Eyraud, J. Heinz, and A. Jardine). submitted.

Quantifier-Free Graph Transductions for Root-and-Pattern Morphology. (with H. Dolatian and S. Moradi). under review.

Phonological Complexity Across Speech and Sign. in prep 




How the Constraint Space Structure Enables Learning. NorthEast Computational Phonology Circle 2018. MIT

The Computational Nature of Phonology Across Speech and Sign. Sign Language Research Lab, University of Connecticut 

How the Structure of the Constraint Space Enables Learning. Invited Talk, University of Connecticut 

Tiers and Relativized Locality Across Language Modules. (with T. Graf, A. Aksenova, H. Baek, A. de Santo, H. Dolatian, S. Moradi, S. Yang, and J. Heinz). "Parallels between Phonology and Syntax" Workshop, July 9 2018, Meertens Institute, Amsterdam 

How the Constraint Space Structure Facilitates Learning. (with Jeffrey Heinz, Jane Chandlee, Adam Jardine). Tenth North American Phonology Conference, May 2018, Concordia University, Montreal

The Logical Complexity of Phonology Across Speech and Sign. Invited Talk, Mar. 2018, Institut Jean Nicod, Ecole Normale Superieure, Paris

Phonological Complexity is Subregular: Evidence from Sign Language. The 51st Annual Meeting of the Chicago Linguistic Society, May 2017, University of Chicago. 



Learning within Linguistically Structured Constraint Spaces. (with J. Chandlee, J. Heinz, and A. Jardine). Tokyo Institute of Technology _ Stony Brook Joint Science Meeting, May 2018.

Subregular Complexity Across Speech and Sign. Society for Computation in Linguistics 1st Meeting. Salt Lake City, Jan 2018 

Reconciling Minimum Description Length with Grammar-Independent Complexity Measures. (with Aniello De Santo, and Jeffrey Heinz).  MIT Workshop on Simplicity in Grammar Learning


Computational Neuroscience

Phonology lies at the intersection of linguistics and neurobiology. Phonological rules govern the physical instantiation of thought made in language, and yet phonology is the first completely abstract computational layer that perceptual encoding/decoding must enter. The mapping problem, or instantiating these symbolic rules into neuronal systems, is an important part of figuring out the biological capacity for language. How brains perform this feat is a matter of their unique structure and computing power, most of which is an open question. 


Quantified Sentences as a Window into Prediction and Priming. (with A. de Santo, J. Drury, and A. Yazdani). to appear in Proceedings of Chicago Linguistics Society 54th Annual Meeting

Homeostasis in Harmonic Grammar. MS, Higher School of Economics, 2016

Second-Language Phonology Learning and Neuroplasticity. Linguistic Portfolios Vol. 4, 2015 


in prep. Syntax, Prosody, and Neural Oscillatory Computation

in prep  Homeostatic Influences on learning Maximum Entropy Grammars. (with b. Gutkin)



Quantified Sentences as a Window into Prediction and Priming. (with A. de Santo, J. Drury, and A. Yazdani). Chicago Linguistics Society 54th Annual Meeting, Chicago, Illinois, April 2018

Homeostatic Reinforcement Learning for Harmonic Grammars. SYNC Conference. CUNY, New York.
Homeostatic Reinforcement Learning for Harmonic Grammars. (with B. Gutkin). Invited Talk. MIT Linguistics Dept., November 2016
Homeostasis in Harmonic Grammar. Invited Talk. Laboratoire de Neurosciences Cognitives, Ecole Normale Superieure, Paris, France, April 2016 

Linguistic Structure from Neural Computation. Talk. Center for Cognition Seminar, Higher School of Economics, 2015.



ERP Effects for Quanitifier Complexity, Priming, and Truth Value in an auditory/visual Verification Task. (with A. de Santo and J. Drury). Society for the Neurobiology of Language Annual Meeting 2017

A Homeostatic Space for OT Phonology. Poster. Pronouns: Syntax, Semantics, Processing Conference (Moscow, Russia)



Pirates and Emperors: On Publishers, Journalists, and Academic Elites. Talk at the New School for Social Research, March 2018

A Dangerous Nuclear Ignorance. Article in Counterpunch Magazine, August 2017